IN.Rmd

---
title: "Indiana Early Voting Statistics"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(knitr)
library(kableExtra)
library(scales)

state_stats <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/2020G_Early_Vote.csv")

# Setup

party_shell <- data.frame(Party=character(),
                                  Count=integer(),
                                  Percent=double(),
                                  stringsAsFactors=FALSE)
party_shell[1,1] <- "Democrats"
party_shell[2,1] <- "Republicans"
party_shell[3,1] <- "Minor"
party_shell[4,1] <- "No Party Affiliation"
party_shell[5,1] <- "TOTAL"

race_shell <- data.frame(Race=character(),
                                  Count=integer(),
                                  Percent=double(),
                                  stringsAsFactors=FALSE)
race_shell[1,1] <- "Non-Hispanic White"
race_shell[2,1] <- "Non-Hispanic Black"
race_shell[3,1] <- "Hispanic"
race_shell[4,1] <- "Non-Hispanic Asian American"
race_shell[5,1] <- "Non-Hispanic Native American"
race_shell[6,1] <- "Other/Multiple/Unknown"
race_shell[7,1] <- "TOTAL"


gender_shell <- data.frame(Gender=character(),
                                  Count=integer(),
                                  Percent=double(),
                                  stringsAsFactors=FALSE)
gender_shell[1,1] <- "Female"
gender_shell[2,1] <- "Male"
gender_shell[3,1] <- "Unknown"
gender_shell[4,1] <- "TOTAL"

age_shell <- data.frame(Age=character(),
                                  Count=integer(),
                                  Percent=double(),
                                  stringsAsFactors=FALSE)
age_shell[1,1] <- "18 to 24"
age_shell[2,1] <- "25 to 34"
age_shell[3,1] <- "35 to 44"
age_shell[4,1] <- "45 to 54"
age_shell[5,1] <- "55 to 64"
age_shell[6,1] <- "65 and up"
age_shell[7,1] <- "TOTAL"

# Indiana

IN_req_send_tot <- data.frame(Total=character(),
                                  Count=integer(),
                                  Percent=double(),
                                  stringsAsFactors=FALSE)

IN_req_send_tot[1,1] <- "TOTAL"
IN_req_send_tot[1,2] <- sum(state_stats[15,5]) 

IN_req_send_tot$Percent <- 100.0

IN_inperson_tot <- data.frame(Total=character(),
                                  Count=integer(),
                                  Percent=double(),
                                  stringsAsFactors=FALSE)

IN_inperson_tot[1,1] <- "TOTAL"
IN_inperson_tot[1,2] <- sum(state_stats[15,7]) 

IN_inperson_tot$Percent <- 100.0

```
## {.tabset}
Last Report: `r state_stats[15,9]`  
Source:  `r state_stats[15,2]`

Total Early Votes: **`r format(as.numeric(state_stats[15,8]), big.mark =",")`**

### In-Person Early Votes

In-Person Early Votes: **`r format(as.numeric(state_stats[15,7]), big.mark =",")`**

### Mail Ballots Returned

Ballots Returned: **`r format(as.numeric(state_stats[15,6]), big.mark =",")`**

### Mail Ballots Requested

Ballots Requested: **`r format(as.numeric(state_stats[15,5]), big.mark =",")`**